• Open Access

Scaling up the lattice dynamics of amorphous materials by orders of magnitude

Ivan Kriuchevskyi, Vladimir V. Palyulin, Rico Milkus, Robert M. Elder, Timothy W. Sirk, and Alessio Zaccone
Phys. Rev. B 102, 024108 – Published 22 July 2020

Abstract

We generalize the nonaffine theory of viscoelasticity for use with large, well-sampled systems of arbitrary chemical complexity. Having in mind predictions of mechanical and vibrational properties of amorphous systems with atomistic resolution, we propose an extension of the kernel polynomial method (KPM) for the computation of the vibrational density of states and the eigenmodes, including the Γ correlator of the affine force field, which is a key ingredient of lattice-dynamic calculations of viscoelasticity. We show that the results converge well to the solution obtained by direct diagonalization (DD) of the Hessian (dynamical) matrix. As is well known, the DD approach has prohibitively high computational requirements for systems with N=104 atoms or larger. Instead, the KPM approach developed here allows one to scale up lattice dynamic calculations of real materials up to 106 atoms, with a hugely more favorable (linear) scaling of computation time and memory consumption with N.

  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Received 4 April 2020
  • Accepted 29 June 2020

DOI:https://doi.org/10.1103/PhysRevB.102.024108

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied PhysicsPolymers & Soft MatterStatistical Physics & Thermodynamics

Authors & Affiliations

Ivan Kriuchevskyi1, Vladimir V. Palyulin2, Rico Milkus3, Robert M. Elder4,5,6, Timothy W. Sirk4, and Alessio Zaccone1,3

  • 1Department of Physics “A. Pontremoli”, University of Milan, via Celoria 16, 20133 Milan, Italy
  • 2Centre for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Nobelya Ulitsa 3, Moscow, 121205, Russia
  • 3Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, United Kingdom
  • 4Polymers Branch, U.S. Army Research Laboratory, Aberdeen Proving Ground, Maryland 20783, USA
  • 5Bennett Aerospace, Inc., Cary, North Carolina 27518, USA
  • 6Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland 20903, USA

Article Text

Click to Expand

References

Click to Expand
Issue

Vol. 102, Iss. 2 — 1 July 2020

Reuse & Permissions
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review B

Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

×

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×